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Least-Squares Methods for Linear Programming Problems: Theory and Applications - Softcover

 
9783844383034: Least-Squares Methods for Linear Programming Problems: Theory and Applications

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Linear programming has evolved over the years, due tosustained research and testing,as an excellent mathematical tool for solving manytheoretical and practical problems.Yet, escalating problem sizes in practical problemspose serious challenges for the verybest linear programming codes, running on the fastestcomputing hardware. New linearprogramming solution techniques have to developed tomeet these challenges. Theresearch performed in this book intends to addressthis issue through a comprehensivestudy of least-squares methods for solving linearprogramming problems.We have developed two new linear programmingalgorithms based on least-squarestheory. A Combined Objectives Least-Squares (COLS)algorithm uses a Non-NegativeLeast-Squares (NNLS) algorithm framework for solvingboth the Phase I and Phase IIlinear programming problems. A Least-SquaresPrimal-Dual (LSPD) algorithm usesNNLS solutions by solving small NNLS problems tosolve relatively larger linear programmingproblems. These algorithms are impervious todegeneracy. Computationalresults for the algorithms shows a superiorperformance over the simplex algorithmon a wide range of linear programming problems.

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About the Author

Balaji Gopalakrishnan earned his doctorate degree in Algorithms, Combinatorics, and Optimization from the School of Industrial and Systems Engineering at Georgia Institute of Technology in 2002. His Ph.D. thesis focused on least-squares properties and related algorithms for linear programming and network flow problems.

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  • PublisherLAP LAMBERT Academic Publishing
  • Publication date2011
  • ISBN 10 3844383034
  • ISBN 13 9783844383034
  • BindingPaperback
  • LanguageEnglish
  • Number of pages124

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Linear programming has evolved over the years, due tosustained research and testing,as an excellent mathematical tool for solving manytheoretical and practical problems.Yet, escalating problem sizes in practical problemspose serious challenges for the verybest linear programming codes, running on the fastestcomputing hardware. New linearprogramming solution techniques have to developed tomeet these challenges. Theresearch performed in this book intends to addressthis issue through a comprehensivestudy of least-squares methods for solving linearprogramming problems.We have developed two new linear programmingalgorithms based on least-squarestheory. A Combined Objectives Least-Squares (COLS)algorithm uses a Non-NegativeLeast-Squares (NNLS) algorithm framework for solvingboth the Phase I and Phase IIlinear programming problems. A Least-SquaresPrimal-Dual (LSPD) algorithm usesNNLS solutions by solving small NNLS problems tosolve relatively larger linear programmingproblems. These algorithms are impervious todegeneracy. Computationalresults for the algorithms shows a superiorperformance over the simplex algorithmon a wide range of linear programming problems. 124 pp. Englisch. Seller Inventory # 9783844383034

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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Linear programming has evolved over the years, due tosustained research and testing,as an excellent mathematical tool for solving manytheoretical and practical problems.Yet, escalating problem sizes in practical problemspose serious challenges for the verybest linear programming codes, running on the fastestcomputing hardware. New linearprogramming solution techniques have to developed tomeet these challenges. Theresearch performed in this book intends to addressthis issue through a comprehensivestudy of least-squares methods for solving linearprogramming problems.We have developed two new linear programmingalgorithms based on least-squarestheory. A Combined Objectives Least-Squares (COLS)algorithm uses a Non-NegativeLeast-Squares (NNLS) algorithm framework for solvingboth the Phase I and Phase IIlinear programming problems. A Least-SquaresPrimal-Dual (LSPD) algorithm usesNNLS solutions by solving small NNLS problems tosolve relatively larger linear programmingproblems. These algorithms are impervious todegeneracy. Computationalresults for the algorithms shows a superiorperformance over the simplex algorithmon a wide range of linear programming problems. Seller Inventory # 9783844383034

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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Gopalakrishnan BalajiBalaji Gopalakrishnan earned his doctorate degree in Algorithms, Combinatorics, and Optimization from the School of Industrial and Systems Engineering at Georgia Institute of Technology in 2002. His Ph.D. thesis . Seller Inventory # 5475830

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